The use of stereoscopy in fine arts enabled artists to create paintings and drawings that could detach from the flat surfaces they were laid on and float directly in front of the observer's eyes, opening a whole new world of possibilities for artistic experimentation. In the digital era, abundant computational methods have been developed to create monoscopic images that resemble artwork, using as an input either 3D models or images. Despite the high availability of such algorithms, hardly any research has been done so far in the area of artistic stereoscopic rendering from real images. The work presented in this dissertation provides a stepping stone in the direction of combining computer graphics and vision techniques to form novel image-based stereoscopic Non-Photorealistic Rendering algorithms. These algorithms can be used to transform photographic stereoscopic images into pairs of pictures that resemble stereoscopic drawings, cartoons or paintings.

Furthermore, the artistic-looking stereoscopic image pairs generated using our algorithms provide a basis over which a set of interactive methods and tools are built to enhance the experience of viewers. The novel algorithms presented in this work set the foundation to harnessing stereoscopy as an artistic medium within the context of image-based computer graphics and vision, and their results may find utility in the game, media or film industries.